Rows: 1,806,544
Columns: 14
$ atc <chr> "A", "A", "A", "A", "A", "A", "A", "A", "A", …
$ year <dbl> 2023, 2023, 2023, 2023, 2023, 2023, 2023, 202…
$ sector <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ region <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ sex <chr> "2", "1", "0", "2", "1", "0", "2", "1", "0", …
$ agegroup <chr> "00-17", "00-17", "00-17", "18-24", "18-24", …
$ count_persons <dbl> 25116, 21962, 47080, 23313, 13137, 36450, 124…
$ count_persons_per1kpop <dbl> 44.61, 37.04, 40.73, 92.26, 50.10, 70.79, 169…
$ turnover <dbl> 32451, 40295, 72746, 51797, 29808, 81606, 419…
$ reimbursement <dbl> 21308, 29871, 51179, 21707, 15882, 37590, 104…
$ sold_amount <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
$ sold_amount_1kpop_day <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
$ personreferabledata_perc <chr> "94", "94", "94", "94", "94", "94", "94", "94…
$ NA <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…